"""Markdown content parser and excerpt extraction utilities."""

from __future__ import annotations

import re


def strip_markdown(markdown_text: str) -> str:
    """Remove markdown syntax markers (headers, bold, italics, links, code blocks) to obtain plain text."""
    if not markdown_text:
        return ""

    text = markdown_text

    # Remove code blocks
    text = re.sub(r"```[\s\S]*?```", " ", text)
    text = re.sub(r"`[^`]*`", " ", text)

    # Remove headers (# Header)
    text = re.sub(r"^#+\s+", " ", text, flags=re.MULTILINE)

    # Replace markdown links [anchor](url) with just anchor
    text = re.sub(r"\[([^\]]+)\]\([^)]+\)", r"\1", text)

    # Remove image links ![alt](url)
    text = re.sub(r"!\[[^\]]*\]\([^)]+\)", " ", text)

    # Remove bold/italics (*, _, **, __)
    text = re.sub(r"(\*\*|__)(.*?)\1", r"\2", text)
    text = re.sub(r"(\*|_)(.*?)\1", r"\2", text)

    # Remove blockquotes and list markers
    text = re.sub(r"^\s*[-*+]\s+", " ", text, flags=re.MULTILINE)
    text = re.sub(r"^\s*\d+\.\s+", " ", text, flags=re.MULTILINE)
    text = re.sub(r"^\s*>\s*", " ", text, flags=re.MULTILINE)

    # Normalize whitespace
    text = re.sub(r"\s+", " ", text).strip()
    return text


def extract_sentences(text: str) -> list[str]:
    """Split text into individual sentences."""
    # Split by period, exclamation, question mark followed by space or newline
    raw_sentences = re.split(r"(?<=[.!?])\s+", text.strip())
    sentences = [s.strip() for s in raw_sentences if len(s.strip()) > 3]
    return sentences


def extract_evidence_snippets(
    markdown_text: str, match_terms: list[str], max_snippets: int = 3
) -> list[str]:
    """
    Extract relevant sentence excerpts from Markdown text that contain any of the given match terms.
    Preserves original phrasing and formats as clean evidence.
    """
    if not markdown_text or not match_terms:
        return []

    plain_text = strip_markdown(markdown_text)
    sentences = extract_sentences(plain_text)
    if not sentences:
        sentences = [plain_text]

    lower_terms = [t.lower() for t in match_terms if t]
    evidence: list[str] = []

    for sentence in sentences:
        lower_sent = sentence.lower()
        for term in lower_terms:
            if re.search(r"\b" + re.escape(term) + r"\b", lower_sent) or term in lower_sent:
                clean_snippet = sentence.strip()
                if clean_snippet and clean_snippet not in evidence:
                    evidence.append(clean_snippet)
                    if len(evidence) >= max_snippets:
                        return evidence
                break

    return evidence